A strong foundation in mathematical skills is critical for both academic success and for quantitative reasoning in everyday life. Deficiencies in these skills can impair academic skill development and limit future job opportunities in adulthood. Although the consequences of poor numeracy are substantial, little is known about the neurobiological basis of typical and atypical changes in mathematical skill development over time. Mathematical disability (MD) can be defined by stable low achievement over multiple time points, and has been hypothesized to be accompanied by structural and functional aberrations in the posterior parietal cortex. Surprisingly, many children score poorly at one time point, only to rebound at the next. What underlies this variation in the trajectory of math achievement across individual children? The overarching goal of my proposed work is to examine the cognitive and neural profile of persistent low math skills from childhood to adolescence. A unique longitudinal cohort of children with MD acquired at Stanford will be combined with state-of-the-art brain imaging of brain structure and function. Standardized behavioral measures of math skills during a critical time window for math skill acquisition (ages 7 - 9) will be used to identify subsets of children who (1) are typically developing (TD), (2) start as MD but recover their math skills over time (MD Gainers) and (3) persist with math disability over time (Persistent MD). I will examine the behavior, structural and functional brain profile of these groups at two points during childhood and then again during adolescence (ages 15 - 17), characterizing individual differences in longitudinal change in math skills and determine the long-term outcome of children that show persistent deficits compared to those that improve over time. The structural and functional brain bases for these different trajectories will be characterized using anatomical and functional MRI methodologies to determine why some children improve over time while others show persistent deficits, and predictive algorithms will be utilized to identify biomarkers of Persistent MD. The proposed research has broad implications for improving learning in children with math learning disabilities. The proposed studies are highly relevant to the mission of the NIH Program Announcement Development of Mathematical Cognition and Reasoning and the Prevention of Math Learning Disabilities (PA-12-248). The proposed work will provide important new insights into (1) brain plasticity in children with MD and their TD peers, (2) the neurobiological basis of persistent MD from childhood to adolescence and (3) ways to predict which children with MD will show persistent deficits into adolescence. This work will also eventually aid in the early identification of children with persistent MD who might beneft from targeted interventions.